Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early‐Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study

列线图 医学 腺鳞癌 放射科 阶段(地层学) 腺癌 肿瘤科 内科学 癌症 古生物学 生物
作者
Mei Xiao,Ting Qian,Le Fu,Wei Yan,Hua Feng,Wei Yong Gu,Hai Ming Li,Yong Ai Li,Zhao Qian,Jie Cheng,Guofu Zhang,Jinwei Qiang
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:59 (4): 1394-1406 被引量:8
标识
DOI:10.1002/jmri.28882
摘要

Background Deep stromal invasion (DSI) is one of the predominant risk factors that determined the types of radical hysterectomy (RH). Thus, the accurate assessment of DSI in cervical adenocarcinoma (AC)/adenosquamous carcinoma (ASC) can facilitate optimal therapy decision. Purpose To develop a nomogram to identify DSI in cervical AC/ASC. Study Type Retrospective. Population Six hundred and fifty patients (mean age of 48.2 years) were collected from center 1 (primary cohort, 536), centers 2 and 3 (external validation cohorts 1 and 2, 62 and 52). Field Strength/Sequence 5‐T , T2 ‐weighted imaging ( T2WI , SE / FSE ), diffusion‐weighted imaging ( DWI , EPI ), and contrast‐enhanced T1 ‐weighted imaging ( CE‐T1WI , VIBE / LAVA ). Assessment The DSI was defined as the outer 1/3 stromal invasion on pathology. The region of interest (ROI) contained the tumor and 3 mm peritumoral area. The ROIs of T2WI, DWI, and CE‐T1WI were separately imported into Resnet18 to calculate the DL scores (TDS, DDS, and CDS). The clinical characteristics were retrieved from medical records or MRI data assessment. The clinical model and nomogram were constructed by integrating clinical independent risk factors only and further combining DL scores based on primary cohort and were validated in two external validation cohorts. Statistical Tests Student's t ‐test, Mann–Whitney U test, or Chi‐squared test were used to compare differences in continuous or categorical variables between DSI‐positive and DSI‐negative groups. DeLong test was used to compare AU‐ROC values of DL scores, clinical model, and nomogram. Results The nomogram integrating menopause, disruption of cervical stromal ring (DCSRMR), DDS, and TDS achieved AU‐ROCs of 0.933, 0.807, and 0.817 in evaluating DSI in primary and external validation cohorts. The nomogram had superior diagnostic ability to clinical model and DL scores in primary cohort (all P < 0.0125 [0.05/4]) and CDS ( P = 0.009) in external validation cohort 2. Data Conclusion The nomogram achieved good performance for evaluating DSI in cervical AC/ASC. Level of Evidence 3 Technical Efficacy Stage 2
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
hanlixuan完成签到 ,获得积分10
1秒前
keleboys完成签到 ,获得积分10
1秒前
xinqisusu完成签到 ,获得积分10
3秒前
昔昔完成签到 ,获得积分10
6秒前
LRR完成签到 ,获得积分10
11秒前
davis264完成签到,获得积分10
11秒前
11秒前
huahua完成签到 ,获得积分10
14秒前
make217完成签到 ,获得积分10
16秒前
biopig完成签到,获得积分0
18秒前
sxc完成签到 ,获得积分10
20秒前
Wtony完成签到 ,获得积分10
20秒前
波里舞完成签到 ,获得积分10
21秒前
内向苡完成签到,获得积分10
21秒前
爱马仕完成签到,获得积分10
23秒前
27秒前
哈哈完成签到 ,获得积分10
28秒前
fearlessji完成签到 ,获得积分10
30秒前
默默发布了新的文献求助10
31秒前
tingalan应助科研通管家采纳,获得10
32秒前
搜集达人应助科研通管家采纳,获得10
32秒前
李爱国应助daguan采纳,获得10
36秒前
小草完成签到 ,获得积分10
40秒前
CandyJump完成签到,获得积分10
41秒前
巨大的小侠完成签到 ,获得积分10
43秒前
Mint完成签到 ,获得积分10
45秒前
鱼儿游啊游完成签到,获得积分10
46秒前
飞快的雁完成签到 ,获得积分10
47秒前
67完成签到,获得积分10
47秒前
杰小瑞完成签到,获得积分10
53秒前
HY完成签到,获得积分10
53秒前
孙不缺发布了新的文献求助10
55秒前
研友_LMg3PZ完成签到,获得积分10
55秒前
ZaZa完成签到,获得积分10
57秒前
LS完成签到,获得积分10
58秒前
narthon完成签到 ,获得积分10
1分钟前
1分钟前
钱学森完成签到,获得积分10
1分钟前
GRATE完成签到 ,获得积分10
1分钟前
454simba完成签到 ,获得积分10
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de guyane 2500
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Campbell Walsh Wein Urology 3-Volume Set 12th Edition 200
Three-dimensional virtual model for robot-assisted partial nephrectomy in totally endophytic renal tumors: a propensity-score matching analysis with a control group 200
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5866712
求助须知:如何正确求助?哪些是违规求助? 6426461
关于积分的说明 15654910
捐赠科研通 4981701
什么是DOI,文献DOI怎么找? 2686725
邀请新用户注册赠送积分活动 1629535
关于科研通互助平台的介绍 1587532